Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
P49593

UPID:
PPM1F_HUMAN

ALTERNATIVE NAMES:
Ca(2+)/calmodulin-dependent protein kinase phosphatase; Partner of PIX 2; Protein fem-2 homolog

ALTERNATIVE UPACC:
P49593; A8K6G3; B7Z2C3; Q96PM2

BACKGROUND:
The enzyme Protein phosphatase 1F, recognized by its alternative names such as Ca(2+)/calmodulin-dependent protein kinase phosphatase, is pivotal in the deactivation of CaM-kinases II, IV, and I. This action is essential for the regulation of calcium signaling pathways and the promotion of apoptosis, indicating its significant role in cellular function and signaling.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Protein phosphatase 1F offers a promising avenue for the development of novel therapeutic approaches. Its critical role in modulating calcium signaling and apoptosis presents it as a valuable target for therapeutic intervention in related disorders.

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